class: center, middle, inverse, title-slide # Forecasting and Risk ### .font150[BANA 4090] ### 08/25/2022 --- # About me </br> .pull-left[ </br> <!--- https://slideplayer.com/slide/7417023/ My name is ZhaohuJonathan Fan. I go by JOnathan and I am a ...... --> .center[ <img src="images/JF.PNG" width="260" height="260" > ] ] .pull-right[ </br> </br> </br> </br> .font100[ - Ph.D. Candidate in Business Analytics. - Applied statistician, business practitioner. - Foodie and more.... 😄 ] ] --- # About you </br> </br> .font120[ - What are you reading right now? ] .font120[ - What type of job do you hope to hire into after program? ] .font120[ - What industry do you hope to work within after the program? ] .font120[ - What is your experience with R programming? ] --- # What this course is about </br> </br> </br> </br> - .font150[ Thinking with Data ] - .font150[ Storytelling with Data ] --- # Objectives </br> </br> - .font100[ Have fun – approach analytics with curiosity and collaboration ] - .font100[ Equip students with proper foundation to approach data analysis and data-driven projects - Framework for approaching analytics projects - Understanding of traditional and modern approaches to analytics - Exposure to common challenges within business and how to overcome ] - .font100[ Provide of project for portfolio ] - .font100[ Practice with R programming language as it relates to data ] --- # Teaching principles </br> </br> - .font100[ Focus on what you need to succeed in the workplace ] - .font100[ Learn through practice and discussion – Labs, consistent datasets as we learn ] - .font100[ Interesting problem – Real-world Project ] --- name: course-introduction class: clear, center,middle .font200[ Part 1: Introduction ] --- # Data science pipeline .center[ <img src="images/tidy11.PNG" width="937" height="368" > ] - .font100[ Tidyverse packages include all the packages required in the data science workflow, ranging from data exploration to data visualization. ] --- # R: Hello, world! <!--- Over the years, Python has become increasingly versatile as a coding language. From basic programs such as printing the phrase “Hello world!” to being used in data science and machine learning, more and more Python libraries and applications are being expanded by open-source contributors and used across different industries. --> <!---Python vs. R for Data Science Important notes for Python and R--> .pull-left[ .font180[ .blue[Output] ] .code150[ ``` ## [1] "Hello World!" ``` ``` ## [1] 15 ``` ``` ] ] .pull-right[ .font180[ .purple[Code] ] .code120[ ```R *print("Hello, world!") x <- 10 y = 5 *x+y ``` ] ] --- class: clear,middle,center .font200[ Questions? 😄 ]